Combining Group Contribution Method and Semisupervised Learning to Build Machine Learning Models for Predicting Hydroxyl Radical Rate Constants of Water Contaminants

Combining Group Contribution Method and Semisupervised Learning to Build Machine Learning Models for Predicting Hydroxyl Radical Rate Constants of Water Contaminants

Machine learning is an effective tool for predicting reaction rate constants for many organic compounds with the hydroxyl radical (HO ). Previously reported models have achieved relatively good performance, but due to scarce data (

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Veröffentlicht in:Environmental science & technology 2024-12
Hauptverfasser: Liu, Zhao, Shang, Lanyu, Huang, Kuan, Yue, Zhenrui, Han, Alan Y, Wang, Dong, Zhang, Huichun
Format: Artikel
Sprache:eng
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Zusammenfassung:Machine learning is an effective tool for predicting reaction rate constants for many organic compounds with the hydroxyl radical (HO ). Previously reported models have achieved relatively good performance, but due to scarce data (
ISSN:0013-936X
1520-5851
1520-5851
DOI:10.1021/acs.est.4c11950